Good visual displays uncover patterns quantitative scientists might otherwise miss, and can make or break a paper. This course takes the design of graphics and tables seriously, and surveys a variety of visual techniques for exploring data and summarizing statistical models. Emphasis on principles of effective visualization, novel visual displays, examples from the social sciences, and implementation of recommended techniques in R.

This is a 9-hour short course version of the full Data Visualization course; the lectures for the full term course are below. Students taking the short course will also need these additional resources:

We will examine two R scripts: a script using the base R graphics to show confidence intervals around a regression line, and another script using grid R graphics to accomplish the same task. A third, more advanced grid graphics script replaces ticks with gridlines and packs the grid graphics code inside a more general and usable function, contained in this required helper file. The final graphic can be viewed here. All three scripts require this dataset. Interested students can find detailed instructions for downloading, installing, and learning my recommended software for quantitative social science here. Focus on steps 1.1 and 1.3 for now, and then, optionally, step 1.2.

Making ropeladder plots to show model robustness using crime data: Rcode.

Topic 7

Interactive Visual Displays with R + Shiny

The Shiny package makes it easy to convert your R code and graphics, including those made with the tile package, into interactive displays for the web. We’ll work through the written Shiny tutorial at the bottom of this page. We will discuss several other examples in class, including this example from your instructor using tile and Shiny to show who got the most medals in the Olympics using different medal aggregation formulas. The underlying code for the example is in this zip archive; feel free to study the code and come to class with questions.

Topic 8

Advanced Latex for Scientific Typesetting

Time permitting, we will consider the use of modern Latex typesetting tools, especially Xetex and the fontspec package. We’ll discuss my caxetexFree stylesheet (manual; .sty file). Students new to Latex should read the Not So Short Introduction to Latex first.

Students will join a small group to discuss a visual display problem of common interest; creation and organization of these groups to be coordinated through the web. Students will write a 1-2 page memo before the first group meeting, and each group will write a 5+ page essay for the class on what they have learned, to be distributed by 20 February. Groups will answer questions from the class during the week of 20 February. See the syllabus for further details.

Final Poster

Presented during the final three to five classes

On an assigned day during the last two weeks of the course, each student will present a poster applying the tools learned in class to their own research. Alternatively, students can take an article published in their field and show how better visuals would either more clearly convey the findings or cast doubt on them. The final presentation may address problems raised in the breakout session or problem sets, but it is usually more fruitful for students to tackle a new problem.